Data Engineer AI Java/Python/Spark

Role Overview:

We are looking for a Senior/Lead Data & GenAI Engineer to design, build and maintain scalable, production-grade data and AI platforms.

The role combines software engineering, distributed data processing, cloud-native technologies and Generative AI. You will work across teams, drive technical initiatives and build reusable libraries and frameworks that enable reliable, scalable and testable systems.

Key Responsibilities:

• Develop, test and maintain high-quality, production-ready software.
• Design and implement large-scale data pipelines and distributed processing systems.
• Build scalable cloud-native services and platforms using modern engineering practices.
• Provide technical leadership for cross-team initiatives and complex engineering projects.
• Design and develop reusable libraries, frameworks and platform components.
• Optimize distributed data processing workloads for performance, scalability and reliability.
• Work with data platforms including Databricks, Apache Spark and Snowflake.
• Develop and deploy applications using Python and/or Java.
• Build and operate containerized workloads using Kubernetes and cloud-native technologies.
• Design and implement GenAI/LLM-based applications and services.
• Work with frameworks such as LangChain and LangGraph for LLM orchestration and agentic workflows.
• Collaborate with data scientists, software engineers, architects and product teams.
• Establish engineering best practices around testing, observability, reliability and deployment.

Required Experience:

• 5+ years of professional software/data engineering experience.
• Strong hands-on experience with Python and/or Java.
• Strong experience with Apache Spark and distributed data processing.
• Experience with Databricks and/or modern lakehouse platforms.
• Experience with Snowflake or comparable cloud data warehouses.
• Practical experience with Kubernetes and cloud-native technologies.
• Experience designing and maintaining large-scale data pipelines.
• Strong understanding of distributed systems, scalability and production engineering.
• Experience developing ML/AI or GenAI applications.
• Experience with LLM-based applications, RAG, AI agents or LLM orchestration.
• Familiarity with LangChain, LangGraph or similar GenAI frameworks.
• Strong software engineering fundamentals including testing, code quality and system design.

Nice to Have:

• Experience with AWS, Azure or GCP.
• Experience with streaming technologies such as Kafka.
• Experience with Delta Lake / Lakehouse architecture.
• Experience building RAG pipelines and vector-search solutions.
• Experience with LLM evaluation, observability and productionization.
• Experience with AI agents, tool calling and multi-step workflows.
• Experience building internal developer platforms, frameworks or reusable engineering libraries.
• Experience leading cross-functional or cross-team technical initiatives.

Ideal Candidate Profile:

The strongest candidate is not purely a Data Engineer and not purely an ML Engineer.

We are looking for someone who combines:

Software Engineering + Data Engineering + Cloud/Platform Engineering + GenAI

Typical backgrounds may include:

• Senior Data Engineer
• Lead Data Engineer
• Senior Software Engineer – Data
• Data Platform Engineer
• Senior Cloud Data Engineer
• AI/ML Platform Engineer
• Senior ML Engineer with strong data engineering experience
• GenAI Engineer with strong distributed-data/platform experience
• Data & AI Architect / Technical Lead

Core Technology Stack:

Languages: Python, Java

Data: Apache Spark, Databricks, Snowflake, Delta Lake

Cloud/Platform: Kubernetes, Docker, AWS/Azure/GCP, cloud-native technologies

GenAI/ML: LLMs, RAG, LangChain, LangGraph, AI agents, vector search

Engineering: Distributed systems, APIs, CI/CD, automated testing, observability, scalability